IDEAS home Printed from https://ideas.repec.org/a/spr/cejnor/v29y2021i1d10.1007_s10100-019-00630-3.html
   My bibliography  Save this article

Dynamic programming approach for solving the open shop problem

Author

Listed:
  • Ansis Ozolins

    (University of Latvia)

Abstract

This paper deals with the open shop scheduling problem (OSP) with makespan minimization. An exact dynamic programming algorithm is proposed for solving the OSP to optimality. This approach is applied to the OSP for the first time. Computational results show that the proposed algorithm is able to solve moderate benchmark instances.

Suggested Citation

  • Ansis Ozolins, 2021. "Dynamic programming approach for solving the open shop problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(1), pages 291-306, March.
  • Handle: RePEc:spr:cejnor:v:29:y:2021:i:1:d:10.1007_s10100-019-00630-3
    DOI: 10.1007/s10100-019-00630-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10100-019-00630-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10100-019-00630-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gueret, Christelle & Jussien, Narendra & Prins, Christian, 2000. "Using intelligent backtracking to improve branch-and-bound methods: An application to Open-Shop problems," European Journal of Operational Research, Elsevier, vol. 127(2), pages 344-354, December.
    2. Ansis Ozolins, 2019. "Improved bounded dynamic programming algorithm for solving the blocking flow shop problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(1), pages 15-38, March.
    3. Arnaud Malapert & Hadrien Cambazard & Christelle Guéret & Narendra Jussien & André Langevin & Louis-Martin Rousseau, 2012. "An Optimal Constraint Programming Approach to the Open-Shop Problem," INFORMS Journal on Computing, INFORMS, vol. 24(2), pages 228-244, May.
    4. Taillard, E., 1993. "Benchmarks for basic scheduling problems," European Journal of Operational Research, Elsevier, vol. 64(2), pages 278-285, January.
    5. Christian Prins, 2000. "Competitive genetic algorithms for the open-shop scheduling problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 52(3), pages 389-411, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ahmadian, Mohammad Mahdi & Khatami, Mostafa & Salehipour, Amir & Cheng, T.C.E., 2021. "Four decades of research on the open-shop scheduling problem to minimize the makespan," European Journal of Operational Research, Elsevier, vol. 295(2), pages 399-426.
    2. Arnaud Malapert & Hadrien Cambazard & Christelle Guéret & Narendra Jussien & André Langevin & Louis-Martin Rousseau, 2012. "An Optimal Constraint Programming Approach to the Open-Shop Problem," INFORMS Journal on Computing, INFORMS, vol. 24(2), pages 228-244, May.
    3. Selcuk Colak & Anurag Agarwal, 2005. "Non‐greedy heuristics and augmented neural networks for the open‐shop scheduling problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(7), pages 631-644, October.
    4. Mejía, Gonzalo & Yuraszeck, Francisco, 2020. "A self-tuning variable neighborhood search algorithm and an effective decoding scheme for open shop scheduling problems with travel/setup times," European Journal of Operational Research, Elsevier, vol. 285(2), pages 484-496.
    5. Guillermo Campos Ciro & Frédéric Dugardin & Farouk Yalaoui & Russell Kelly, 2016. "Open shop scheduling problem with a multi-skills resource constraint: a genetic algorithm and an ant colony optimisation approach," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4854-4881, August.
    6. Shahaboddin Shamshirband & Mohammad Shojafar & A. Hosseinabadi & Maryam Kardgar & M. Nasir & Rodina Ahmad, 2015. "OSGA: genetic-based open-shop scheduling with consideration of machine maintenance in small and medium enterprises," Annals of Operations Research, Springer, vol. 229(1), pages 743-758, June.
    7. Bahman Naderi & Rubén Ruiz & Vahid Roshanaei, 2023. "Mixed-Integer Programming vs. Constraint Programming for Shop Scheduling Problems: New Results and Outlook," INFORMS Journal on Computing, INFORMS, vol. 35(4), pages 817-843, July.
    8. Diarmuid Grimes & Emmanuel Hebrard, 2015. "Solving Variants of the Job Shop Scheduling Problem Through Conflict-Directed Search," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 268-284, May.
    9. Schmid, Verena & Doerner, Karl F. & Laporte, Gilbert, 2013. "Rich routing problems arising in supply chain management," European Journal of Operational Research, Elsevier, vol. 224(3), pages 435-448.
    10. Sels, Veronique & Craeymeersch, Kjeld & Vanhoucke, Mario, 2011. "A hybrid single and dual population search procedure for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 215(3), pages 512-523, December.
    11. Pempera, Jaroslaw & Smutnicki, Czeslaw, 2018. "Open shop cyclic scheduling," European Journal of Operational Research, Elsevier, vol. 269(2), pages 773-781.
    12. Shahvari, Omid & Logendran, Rasaratnam, 2016. "Hybrid flow shop batching and scheduling with a bi-criteria objective," International Journal of Production Economics, Elsevier, vol. 179(C), pages 239-258.
    13. Fleming, Christopher L. & Griffis, Stanley E. & Bell, John E., 2013. "The effects of triangle inequality on the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 224(1), pages 1-7.
    14. Jean-Paul Watson & Laura Barbulescu & L. Darrell Whitley & Adele E. Howe, 2002. "Contrasting Structured and Random Permutation Flow-Shop Scheduling Problems: Search-Space Topology and Algorithm Performance," INFORMS Journal on Computing, INFORMS, vol. 14(2), pages 98-123, May.
    15. Nouha Nouri & Talel Ladhari, 2018. "Evolutionary multiobjective optimization for the multi-machine flow shop scheduling problem under blocking," Annals of Operations Research, Springer, vol. 267(1), pages 413-430, August.
    16. Liaw, Ching-Fang, 2000. "A hybrid genetic algorithm for the open shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 124(1), pages 28-42, July.
    17. Pflughoeft, K. A. & Hutchinson, G. K. & Nazareth, D. L., 1996. "Intelligent decision support for flexible manufacturing: Design and implementation of a knowledge-based simulator," Omega, Elsevier, vol. 24(3), pages 347-360, June.
    18. Pan, Quan-Ke & Gao, Liang & Li, Xin-Yu & Gao, Kai-Zhou, 2017. "Effective metaheuristics for scheduling a hybrid flowshop with sequence-dependent setup times," Applied Mathematics and Computation, Elsevier, vol. 303(C), pages 89-112.
    19. Perez-Gonzalez, Paz & Framinan, Jose M., 2024. "A review and classification on distributed permutation flowshop scheduling problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 1-21.
    20. Liu, Jiyin & Reeves, Colin R, 2001. "Constructive and composite heuristic solutions to the P//[summation operator]Ci scheduling problem," European Journal of Operational Research, Elsevier, vol. 132(2), pages 439-452, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:cejnor:v:29:y:2021:i:1:d:10.1007_s10100-019-00630-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.